The race to anticipate what shoppers want before they even know it themselves has become the new battleground in retail. As consumer preferences shift faster than ever and competition intensifies across physical and digital channels, major retailers are turning to artificial intelligence not just as a support tool but as a core driver of business strategy. The goal is straightforward: compress the time between spotting a trend and getting products on shelves while making the shopping experience feel seamless across every touchpoint .
Target’s recent commitment to invest over $2 billion in operational and capital improvements this year illustrates how seriously legacy retailers are taking the technology transformation challenge . The Minneapolis-based chain, which saw sales decline 1.7% last year to $104.8 billion, is betting that AI can help reverse its fortunes and restore growth in a market where even slight delays in reading consumer sentiment can mean lost revenue . CEO Michael Fiddelke has made technology investment central to his turnaround strategy, arguing that these tools directly translate to better experiences whether customers shop online or walk through store aisles .
Reading Fashion Trends Before They Peak
Understanding what styles will resonate with shoppers months before a season starts has always been part art and part guesswork. Target’s apparel division now relies on an internal platform called Trend Brain, which combines visual analysis of fashion imagery with sentiment data pulled from social media to generate early signals about emerging trends . The system allows design teams to move significantly faster, rotating collections at nearly double the previous pace and giving merchandisers time to adjust orders before committing fully to a direction .
Gena Fox, who leads apparel at Target, shared that the platform flagged an early uptick in interest around polka dot patterns, allowing the team to increase inventory for that aesthetic before it became mainstream . That kind of advance notice changes how buyers allocate budgets and how marketing teams prepare campaigns. Instead of reacting to what’s already popular, retailers can position themselves ahead of the curve, creating the perception that they understand their customer base more intimately than competitors do.
The integration of trend prediction into merchandising also shortens the feedback loop between design, production, and promotion. When teams know earlier that a product might underperform, they can pivot resources toward stronger opportunities without waiting for disappointing sales data to force the decision . This compressed timeline helps align storytelling, seasonal launches, and product assortments in ways that feel more cohesive to shoppers.
Simplifying Operations on the Store Floor
While much of the conversation around retail technology focuses on customer-facing apps and online personalization, operational efficiency inside stores remains critical to profitability. Target has equipped managers and frontline associates with custom tools running on Zebra handheld devices, designed to streamline tasks like setting up displays, accessing inventory information, and requesting support without needing to return to a back-office computer . The intent is to reduce the minutes spent on administrative work and redirect that capacity toward assisting customers directly.
Fiddelke emphasized that investments in these technologies produce measurable returns in customer experience quality, whether the interaction happens digitally or in person . For store staff, having instant access to information means fewer moments of uncertainty when a customer asks about product availability or location. It also means display adjustments and inventory checks happen faster, keeping the sales floor organized and responsive throughout the day.
Accelerating Digital Product Development
Rebuilding a mobile shopping app from the ground up is typically a multi-year undertaking that requires careful coordination across engineering, design, and product teams. Target’s technology division completed a full rewrite of its app codebase in roughly 18 months, a timeline that Prat Vemana, the company’s chief information and product officer, attributed partly to AI-assisted coding tools . The updated app now includes features like a scanner that digitizes handwritten shopping lists and a store mode that maps out where listed items are located within a physical location .
Approximately one-third of customers who shop in Target stores now use the app during their visits, turning their smartphones into navigation and planning aids while they browse . This dual-channel behavior reflects a broader shift in how people approach shopping, blending the convenience of digital information with the immediacy of in-store selection. Retailers that can support this hybrid approach without friction stand to capture more of the customer’s attention and spending.
The company is targeting around 2% net sales growth for the current fiscal year as it works to stabilize performance after a challenging 2025 . The strategy hinges on using data and automation to make faster, more confident decisions across merchandising, store operations, and digital engagement, all while keeping the customer experience feeling personalized rather than mechanical.
